Serial and Parallel Pedagogy in Digital Media Education: An AIGC-Based Framework for Cultivating Critical, Creative, and Presentational Thinking in Student Competition Work

Abstract

The rapid evolution of artificial intelligence-generated content (AIGC) has profoundly transformed digital media education, offering unprecedented opportunities for students to explore creative, analytical, and presentational skills. Traditional pedagogical approaches, however, often fail to fully integrate these emerging technologies with structured instructional strategies, limiting students’ capacity to develop comprehensive competencies required in competitive project-based settings. This paper proposes a novel framework that combines serial and parallel pedagogy with AIGC tools to cultivate critical, creative, and presentational thinking in student competition work. The serial component emphasizes stepwise, scaffolded learning, allowing students to build foundational knowledge and analytical skills sequentially, while the parallel component encourages simultaneous engagement with multiple tasks, promoting divergent thinking and innovative problem-solving. By integrating AIGC tools at each stage, students gain access to advanced content generation capabilities, supporting iterative idea exploration, rapid prototyping, and visually compelling presentations. Preliminary implementation in digital media classrooms demonstrates significant improvements in students’ analytical reasoning, originality of ideas, and communication effectiveness. The framework provides a scalable model for enhancing educational practices, preparing students to excel in competitions and professional creative industries. Implications for curriculum design, pedagogical strategy, and future research are discussed, highlighting the potential of serial-parallel pedagogy combined with AI technologies to redefine learning outcomes in digital media education.